Deeksha Adil

According to our database, Deeksha Adil authored at least 16 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Efficient and Provable Algorithms for Covariate Shift.

Deeksha Adil, Jaroslaw Blasiok

CoRR, February, 2025

Decremental (1+ε)-Approximate Maximum Eigenvector: Dynamic Power Method.

Deeksha Adil, Thatchaphol Saranurak

Proceedings of the 52nd International Colloquium on Automata, Languages, and Programming, 2025

Acceleration Meets Inverse Maintenance: Faster ℓ_∞-Regression.

Deeksha Adil, Shunhua Jiang, Rasmus Kyng

Proceedings of the 52nd International Colloquium on Automata, Languages, and Programming, 2025

2024

Fast Algorithms for <i>ℓ_p</i>-Regression.

Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva

J. ACM, October, 2024

Convex optimization with <i>p</i>-norm oracles.

Deeksha Adil, Brian Bullins, Arun Jambulapati, Aaron Sidford

CoRR, 2024

2022

Fast Algorithms for $\ell_p$-Regression and Other Problems

Deeksha Adil

PhD thesis, 2022

Fast Algorithms for 𝓁_p-Regression.

Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva

CoRR, 2022

Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities.

Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva

CoRR, 2022

2021

Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization.

Deeksha Adil, Brian Bullins, Sushant Sachdeva

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Almost-Linear-Time Weighted 𝓁_p-Norm Solvers in Slightly Dense Graphs via Sparsification.

Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva

Proceedings of the 48th International Colloquium on Automata, Languages, and Programming, 2021

2020

Faster <i>p</i>-norm minimizing flows, via smoothed <i>q</i>-norm problems.

Deeksha Adil, Sushant Sachdeva

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

2019

Faster p-norm minimizing flows, via smoothed q-norm problems.

Deeksha Adil, Sushant Sachdeva

CoRR, 2019

Iterative Refinement for 𝓁_p-norm Regression.

Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva

CoRR, 2019

Iterative Refinement for ℓp-norm Regression.

Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression.

Deeksha Adil, Richard Peng, Sushant Sachdeva

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Parameterized algorithms for stable matching with ties and incomplete lists.

Deeksha Adil, Sushmita Gupta, Sanjukta Roy, Saket Saurabh, Meirav Zehavi

Theor. Comput. Sci., 2018